\chapter*{Abstract}
Software systems are becoming an integral part of everyday life influencing organizational and social activities.  This aggravates the need for a socio-technical perspective for requirements engineering, which allows for modeling and analyzing the composition and interaction of hardware and software components with human and organizational actors.

Socio-technical systems (STS), as opposed to the traditional technical computer base systems, include human agents as an integral part of their structure. One important aspect of an STS is its dynamicity:  an STS operates in a continuous evolving environment and, accordingly, its structure changes dynamically. Unlike the technical based system, an STS has the knowledge of how the system should be used to achieve some organizational objectives, and is normally regulated and constrained by internal organizational rules, external laws and regulations.

In this setting, the thesis aims at developing a framework supporting a system able to self-configure, which is to evolve dynamically in response to changes in its environment. A runtime reconfiguration mechanism will be based on AI planning for generating possible system configurations. In particular, the thesis task is to provide a framework that takes an initial organizational structure, and explores the organizational solution space with the help of AI planning technique. Found candidate solutions are simulated with respect to user-defined set of events to evaluate how these solutions adapt to environment changes. Moreover, these solutions are assessed by quantitative evaluators which are accompanied with the framework as well as user-defined ones. Assessment results are visualized to end-user in tree-structure, table, chart to help for a wise decision.
